{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "30e3a660",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "#  Mplfinance Used To Plot MACD Histogram\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8db0114d",
   "metadata": {},
   "source": [
    "### What is MACD Histogram\n",
    "The MACD histogram is a technical analysis tool that is used to measure the momentum and strength of a financial instrument's price movement. MACD stands for Moving Average Convergence Divergence. It is derived from the MACD line, which is calculated by subtracting the 26-day exponential moving average (EMA) from the 12-day EMA.\n",
    "\n",
    "The MACD histogram represents the difference between the MACD line and its signal line, which is a 9-day EMA of the MACD line. It consists of vertical bars that oscillate above or below the zero line, also known as the centerline."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "026a251c",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "### mplfinance 'yahoo' styles was used to customize:\n",
    "- Type of Plot Use `candle`\n",
    "- MACD Histogram Build With Two Lines MACD Line, Signal Line and Histogram\n",
    "- Background, Grid, and Figure Colors\n",
    "- Grid style\n",
    "- Y-Axis On The Right or Left\n",
    "- Matplotlib Defaults\n",
    "- Histogram\n",
    "- Alpha\n",
    "- Color\n",
    "#### The simplest way to do this is to choose one of the `add_plot` that come packaged with `mplfinance`\n",
    "#### but, as we see below, it is also possible to customize your own `mplfinance styles`.\n",
    "#### Also Other Plot Type Can Be Used\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "821ec5c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import mplfinance as mpf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "86dcb05e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# This allows multiple outputs from a single jupyter notebook cell:\n",
    "from IPython.core.interactiveshell import InteractiveShell\n",
    "InteractiveShell.ast_node_interactivity = \"all\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61bf088e",
   "metadata": {},
   "source": [
    "### Read in daily data for the S&P 500 from November of 2019 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f3228212",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(200, 6)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2003-06-25</th>\n",
       "      <td>20.530001</td>\n",
       "      <td>20.83</td>\n",
       "      <td>19.99</td>\n",
       "      <td>20.040001</td>\n",
       "      <td>13.693501</td>\n",
       "      <td>61250600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003-06-26</th>\n",
       "      <td>20.299999</td>\n",
       "      <td>20.76</td>\n",
       "      <td>20.15</td>\n",
       "      <td>20.629999</td>\n",
       "      <td>14.096654</td>\n",
       "      <td>52904900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open   High    Low      Close  Adj Close    Volume\n",
       "Date                                                               \n",
       "2003-06-25  20.530001  20.83  19.99  20.040001  13.693501  61250600\n",
       "2003-06-26  20.299999  20.76  20.15  20.629999  14.096654  52904900"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2004-04-07</th>\n",
       "      <td>28.08</td>\n",
       "      <td>28.129999</td>\n",
       "      <td>27.480000</td>\n",
       "      <td>27.620001</td>\n",
       "      <td>18.923342</td>\n",
       "      <td>72680200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-04-08</th>\n",
       "      <td>28.08</td>\n",
       "      <td>28.139999</td>\n",
       "      <td>27.200001</td>\n",
       "      <td>27.370001</td>\n",
       "      <td>18.752058</td>\n",
       "      <td>71791400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Open       High        Low      Close  Adj Close    Volume\n",
       "Date                                                                   \n",
       "2004-04-07  28.08  28.129999  27.480000  27.620001  18.923342  72680200\n",
       "2004-04-08  28.08  28.139999  27.200001  27.370001  18.752058  71791400"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idf = pd.read_csv('../data/yahoofinance-INTC-19950101-20040412.csv',index_col=0,parse_dates=True).tail(200)\n",
    "\n",
    "df = idf.copy()\n",
    "df.index.name = 'Date'\n",
    "df.shape\n",
    "df.head(2)\n",
    "df.tail(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "584d26a0",
   "metadata": {},
   "source": [
    "--- \n",
    "**The MACD histogram is calculated as the MACD indicator minus the signal line. Observe that:**\n",
    "\n",
    "- When MACD is above the signal line then the histogram is positive.\n",
    "- When MACD is below the signal line then the histogram is negative.\n",
    "- When the gap between the MACD and its signal line is widest then the histogram registers its highest (or lowest) readings.\n",
    "- The histogram is at zero when MACD and the signal line cross (the signal for trading with the MACD).\n",
    "- The histogram turns back towards the zero line when MACD and the signal line converge, well in advance of them actually crossing.\n",
    "\n",
    "\n",
    "- **Here is Following Calculation:**\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a410f0a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Get the 26-day EMA of the closing price\n",
    "k = df['Close'].ewm(span=12, adjust=False, min_periods=12).mean()\n",
    "\n",
    "#Get the 12-day EMA of the closing price\n",
    "d = df['Close'].ewm(span=26, adjust=False, min_periods=26).mean()\n",
    "\n",
    "#Subtract the 26-day EMA from the 12-Day EMA to get the MACD\n",
    "macd = k - d\n",
    "\n",
    "#Get the 9-Day EMA of the MACD for the Trigger line\n",
    "macd_s = macd.ewm(span=9, adjust=False, min_periods=9).mean()\n",
    "\n",
    "#Calculate the difference between the MACD - Trigger for the Convergence/Divergence value\n",
    "macd_h = macd - macd_s\n",
    "#Add all of our new values for the MACD to the dataframe\n",
    "df['MACD_12_26_9'] = df.index.map(macd)\n",
    "df['MACDh_12_26_9'] = df.index.map(macd_h)\n",
    "df['MACDs_12_26_9'] = df.index.map(macd_s)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e5cf3344",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Generating Colors For Histogram\n",
    "def gen_macd_color(df):\n",
    "    macd_color = []\n",
    "    macd_color.clear()\n",
    "    for i in range (0,len(df[\"MACDh_12_26_9\"])):\n",
    "        if df[\"MACDh_12_26_9\"][i] >= 0 and df[\"MACDh_12_26_9\"][i-1] < df[\"MACDh_12_26_9\"][i]:\n",
    "            macd_color.append('#26A69A')\n",
    "            #print(i,'green')\n",
    "        elif df[\"MACDh_12_26_9\"][i] >= 0 and df[\"MACDh_12_26_9\"][i-1] > df[\"MACDh_12_26_9\"][i]:\n",
    "            macd_color.append('#B2DFDB')\n",
    "            #print(i,'faint green')\n",
    "        elif df[\"MACDh_12_26_9\"][i] < 0 and df[\"MACDh_12_26_9\"][i-1] > df[\"MACDh_12_26_9\"][i] :\n",
    "            #print(i,'red')\n",
    "            macd_color.append('#FF5252')\n",
    "        elif df[\"MACDh_12_26_9\"][i] < 0 and df[\"MACDh_12_26_9\"][i-1] < df[\"MACDh_12_26_9\"][i] :\n",
    "            #print(i,'faint red')\n",
    "            macd_color.append('#FFCDD2')\n",
    "        else:\n",
    "            macd_color.append('#000000')\n",
    "            #print(i,'no')\n",
    "    return macd_color"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "24b7da34",
   "metadata": {},
   "outputs": [],
   "source": [
    "macd = df[['MACD_12_26_9']]\n",
    "histogram = df[['MACDh_12_26_9']]\n",
    "signal = df[['MACDs_12_26_9']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "aa32e15d",
   "metadata": {},
   "outputs": [],
   "source": [
    "macd_color = gen_macd_color(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9bc3f19",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "Let's say we want to plot the Ichimoku Cloud along with the basic OHLCV plot.  \n",
    "\n",
    "We Use `make_addplot()` to create the addplot dict, and pass that into the plot() function:\n",
    "\n",
    "We Use `Color` To Define Line Colors\n",
    "\n",
    "We Use `alpha` To Define Depth Line Color\n",
    "\n",
    "We Use `Panel` To Define MACD with Histogram\n",
    "\n",
    "We Usr `Histogram` For MACD Histogram\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bc7973ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "apds = [\n",
    "    mpf.make_addplot(macd,color='#2962FF', panel=1),\n",
    "    mpf.make_addplot(signal,color='#FF6D00', panel=1),\n",
    "    mpf.make_addplot(histogram,type='bar',width=0.7,panel=1, color=macd_color,alpha=1,secondary_y=True),\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "eac0570a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x1000 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mpf.plot(\n",
    "    df,\n",
    "    volume=True,\n",
    "    type=\"candle\", \n",
    "    style=\"yahoo\",\n",
    "    addplot=apds,\n",
    "    volume_panel=2,\n",
    "    figsize=(20,10)\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aeb8d05b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
